Extreme Weather: When Worlds Collide

Real data — temperature, for instance — are almost always the combination of signal and noise, which we could also refer to as trend and fluctuation. Fluctuations are ubiquitous, they happen all the time. Sometimes they go up, sometimes down, sometimes a little and sometimes a lot, but the one thing they don’t do is stop.

That’s why, even in a stable climate, we’re sure to see extremes. Heat waves will happen. So will floods, drought, and giant storms. It’s the nature of the beast, those things can happen for no apparent reason — for no reason at all, really, just because they are random fluctuations. When extremes arrive, they often bring trouble with them. It’s good to be prepared for such fluctuations, because they’re unavoidable.

How extreme they are, and how often they occur, depends on the nature of the fluctuations. By measuring conditions over long periods of time, we not only get to know what the average conditions are, we also learn about the fluctuations. That enables us to define climate as the mean (average) and variation (fluctuations) of weather.

It can even happen, for no apparent reason, that we suffer an extreme extreme, a fluctuation so severe it’s unlike anything we’ve seen for a very long time, maybe even ever. Such events often bring, not just trouble, but disaster. Maybe even disaster more severe than we’ve seen for a very long time, maybe even ever.

Life can be dangerous, that too is the nature of the beast, and extreme extreme weather fluctuation is one of the greatest dangers. Fortunately such fluctuations are exceedingly rare. A once-in-a-thousand-years heat wave only happens, well, once in a thousand years. On average, that is … we could get two such events in rapid succession just because of (very very) bad luck. Fortunately, such concordances of extreme extremes are very very exceedingly rare.

In just the last decade we’ve seen a number of extreme extremes. Even if we only count the heat waves, recent history is remarkable. Europe in 2003, Australia in 2009 (not once but twice in a single year), Russia in 2010, the U.S. in 2012. And now Australia (again!) in 2013. All these heat waves were extreme, some were extreme extreme, and they all brought disaster. Their frequency is just as remarkable as their severity, having come one after another in rapid succession.

That could be just a coincidence — one hell of a whopper of the worst weather luck imaginable. Thing is, we have this mathematical science called statistics, and it tells us that the odds of that happening just by chance is small. Really really small. Miniscule. Sub-microscopic.

We also have this physical science called climate science. It tells us that we’re changing the climate itself, due to a lot of man-made causes but chiefly dumping immense quantities of greenhouse gases in the atmosphere. Because of that, the average temperature is changing. Temperature (and other weather variables), in addition to undergoing never-ending fluctuation, is also showing a trend — so the mean itself is changing. When that happens, a big fluctuation — not an extreme extreme, just an “ordinary” big one — gets added onto a higher mean value.

Consider the following fluctuations:

The value in 2012 (circled in red) is big. It’s the 2nd-biggest fluctuation of the last 118 years, but it’s just a little bigger (by 0.06 degrees) than the fluctuation in 1934 and quite a bit smaller (by 0.5 degrees) than the fluctuation of 1921. All by itself, that fluctuation is bound to bring trouble — a heat wave, possibly an extensive one, and maybe drought as well. It’s the kind of trouble that we are well advised to be prepared for, because it’s the kind of fluctuation that is sure to happen again and again.

But all by itself, that kind of fluctuation isn’t a disaster. We are prepared for it because we have seen it before. It was, effectively, just as big in 1934 and a lot worse in 1921, which is not so long ago that we’ve forgotten how bad it can get just from random fluctuation. We don’t like it, but we muddle through and recover because just as fluctuations can go far up and can also go far down (which is a different kind of trouble), most of the time they’re near the middle so conditions are near average.

Fluctuation is only part of the story. When we add in the effect of trend, we get annual average temperature for the 48 contiguous states of the U.S.

The 2012 value is now like nothing we’ve seen before. The fluctuation alone was big, but hardly extreme. All alone it was trouble, but not disaster. But when that big fluctuation is added to the substantial trend, it is extreme. It’s more than trouble, it’s disaster. It’s crippling drought, deadly heat wave, a big dent in the corn crop, and terrible wildfires raging out of control.

Just this month, Australians experienced a similar large upward fluctuation in nationwide temperature. Again, all by itself that’s not such a big deal. Heat waves and wildfires happen, and since Australia is a pretty hot place anyway those who live there are well prepared for such fluctuations. But when they are added on top of a substantial trend

it becomes like nothing they’ve seen before. These data only go through 2011, they don’t include 2012 and certainly don’t show the astounding heat of early 2013. But they do reveal the trend, the increase in the average which makes every upward fluctuation far worse than it would have been.

The lesson is this: when trend and fluctuation collide, it creates unprecedented extremes. While extremes are trouble, unprecedented extremes are disaster.

Australia has survived their latest heat wave, albeit with much suffering and horrific wildfires. The U.S. survived our hottest year ever, albeit with much suffering, substantial crop damage, and horrific wildfires. But harken back to the opening paragraph, and recall that fluctuations are ubiquitous, they happen all the time, the one thing they don’t do is stop.

So, extremes are inevitable. That’s a problem, but we already knew that and for the most part we’re prepared. The extreme problem, the one we’re not prepared for, the deadly threat we face, is that the trend isn’t going to stop either. If the post-1975 trend continues in the U.S., this is the future we face:

The dot with a red circle around it is the temperature in 2012. That was a national disaster. Now imagine that the endpoint of the red line, so much hotter than what brought about a national disaster, becomes the norm.

What will life be like when unprecedented disaster becomes the norm? We are not prepared.

Alas, “the post-1975 trend continues in the U.S.” is an optimistic forecast. It only leads to an average temperature anomaly of about +6°F by the year 2100. That’s on the low side of actual forecasts by legitimate climate scientists:

Suppose the average temperature anomaly in the U.S. climbs over 11°F by the year 2100. Consider how bad it already was in 2012. Consider how terrible it will be if we get to 6°F. Now, double that. The devastation boggles the mind.

Now imagine all of that plus one of those big upward fluctuations. The kind that is ubiquitous, the kind that just won’t stop.

Whether we, as a civilization, can even survive such a debacle is in doubt.

WHEN FOOLS FOOL

Perhaps you’re thinking that when fluctuation and trend collide, it creates the kind of event that will motivate people to do something about global warming. Indeed it does.

But as bizarre as it may seem, it also helps deniers who want to deny the problem push their denial story. Let’s take the “post-1975 trend continues in the U.S.” and add some fluctuation onto that trend. I added random noise, with the same standard deviation (the same size) as the actual fluctuations of U.S. temperature. This was the result:

The trend keeps rising, and the fluctuations keep fluctuating, but since they go sometimes up and sometimes down, and since they don’t go as far as the 2012 fluctuation very often, in this particular future scenario the temperature didn’t get as high as it was in 2012 for eighteen years, not breaking the 2012 record until 2031. If this is how the future unfolds — and it could well do so, although it could also reach a new record high well before that — we’ll hear proclamations of “No warming in the U.S. for 18 years!” Oklahoma senator James Inhofe will declare that we’re in a cooling period. Anthony Watts will host a guest article by Chip Knappenberger that U.S. temperature data indicate nothing to worry about. Fox News will give them, and a lot of other crackpots, a national televised forum to spread their propaganda. Imagine if you will, the hubbub in 2022 when, just by accident, the fluctuation goes in the opposite direction to the trend and the so-called “Heartland Institute” buys print ads in the New York Times declaring that the whole global warming idea is a scam, climate scientists are a bunch of frauds, and we should really be worried about the next ice age.

Climate scientists will talk about signal and noise, about how ubiquitous is random fluctuation, about the long-term trend, about fundamental physics. They’ll talk about how bad it’s going to get and how it affects such fundamental issues as food and water. It doesn’t get any more fundamental than that.

Meanwhile, the trend will continue. The fluctuations will continue. Sooner or later, the two will collide. Again.

My father had a ranch by Gann Valley, SD. The records high for the state was recorded by Gann Valley during the Great Depression. Because of bad farming practices, eastern South Dakota had a lot of exposed black soil and dust dunes, so mankind had altered the albedo. The soil is black, very dark. Just might have spiked the local surface temps.

One example is the dramatic change in Arctic sea ice beginning about 1900 CE. Another is that before then Swiss glaciers stopped growing and began shrinking a bit. One would have to collect quite a bit of evidence. An entirely different approach is taken in

It shows that by 1930 the concentration of CO2 was about 305ppm, compared to 275ppm for 1750 and about 395ppm today http://co2now.org/

So the increase in CO2 at the beginning of the 1930s was only one quarter of the increase to date, even though it was 180 years after the industrial revolution, and 80 years before today.

So CO2 would have had some effect, but it would have been relatively small.

There were also some largeish natural factors. In the 19th century there were some large volcanic eruptions – Krakatoa (1883) being the most famous. These had a cooling effect, particularly strong in the couple of years following the eruption. However, the relative absence of major volcanic eruptions would probably have contributed to a relative warming in the first half of the 20th century. I believe there may also have been a solar effect.

hey that a really good point that’s just changed my perception of things – past 2050 EVERY year will be a disaster year, there will be no respite. We’re so use to riding out extremes, we see them as infrequent events to wait out, but I think more need to be made of this point that these event will become permanent, with no respite – imagine now that every year past 2050 be an extreme year, with extreme extreme years and only mildly extreme years, and will never go back to what it was (at least not for many generations) !

We’re on track to seeing the Arctic Ocean ice free in a near term summer. At least a slight possibility that it will happen this year and a fairly high probability that it will happen by the summer of 2016.

Soon after that we are likely to see ice-free summers and year-round lack of sea ice just a few more years later.

All the heat that had been going into melting Arctic ice – what is that extra heat going to do to our climate then? We will be essentially adding energy to the system as we will have used up our reserve of cooling.

Then, what is likely to happen when the next El Nino appears? We’ve been without a nice warm El Nino for a few years. The last really strong El Nino was 1997. What happens if we get the sort of El Nino that we experienced multiple times in the 1980s and 1990s? We’ve put a heck of a lot more energy into the oceans in those intervening years. What if some of that energy pops back out and drives our temps to extreme records?

Yup, somewhere between 6 and 20 years is my guess, but it might be sooner. BTW, they still don’t have electricity in this deep freeze in Staten Island, and for those who say cold is not part of the whole, check out this excellent exposition of sudden stratospheric warming:http://www.bbc.co.uk/weather/features/20998895

.. In our study, we extrapolated an exponential trend for a long time period without considering the practicalities of the system. We found that this resulted in crazy numbers. This came as a big surprise …

What do their numbers look like for:

– Per-capita USA usage?
– Per capita European usage?

Let’s face it, once population has stabilized at 10 billion, and everyone has heated their personal swimming pool and taken their obligatory couple of trips to the moon per year, it gets really hard to see what the extra energy use is going to be for.

More seriously, total energy usage is a bounded problem. This is a good thing, because it means that it is a potentially fixable problem.

“Whether we, as a civilization, can even survive such a debacle is in doubt.”
Very good post and question, tamino. Even if civilization as we know survives to the end of the 21st century –which I sincerely doubt– it seems extremely unlikely to me that it will persist into the 22nd century if current trends hold or worsen. Civilization may not make it even if current temperature trends level off somewhat, imo.
Like Bob Wallace, I’m very concerned on even a much shorter time scale.

I skimmed it, but how many papers can they publish where they completely ignore issues for which they must be aware? Regardless of what their stance on the matter is, they don’t seem to say a word about whether they are subtracting signal. Even if they believe that is a false model, why would it be completely absent from their analysis?

For the sake of discussion of commenters above, I will quote one single section from the J. Atmos. Sci., 70, 3–8. paper.

4. Justification for including the AMO as a regressor
The remaining question is whether the AMO is a natural oscillation or the response to a time-varying anthropogenic forcing. Recently Booth et al. (2012) simulated 76% of the two cycles of the AMO in the industrial era using the Earth system model version of the Hadley Centre Global Environmental Model (HadGEM2-ES) and attributed the North Atlantic variability to the indirect effect of anthropogenic aerosol’s time-varying forcing. However, Zhang et al. (2013) pointed out that the indirect aerosol effects in Booth et al. (2012) are probably overestimated, and the time and spatial signatures in the model’s upper ocean are contrary to the observed.

Using 330 yr of multiproxy data of near-global coverage, Delworth and Mann (2000) found almost 4.5 cycles of the AMO, with 2 cycles in the preindustrial era. Tung and Zhou (2012, manuscript submitted to Proc. Natl. Acad. Sci. USA) found 5 cycles of 70-yr oscillation in the world’s longest instrumental temperature record from central England. These long records argue in favor of the natural and recurrent nature of the AMO. The variability appears to be caused by fluctuations in the thermohaline circulation (Dima and Lohmann 2007; Delworth and Mann 2000; Enfield et al. 2001; Knight et al. 2005; Schlesinger and Ramankutty 1994; Wei and Lohmann 2012; Semenov et al. 2010).

There are a couple realizations of a coupled atmosphere–ocean general circulation model calculation containing an AMO of the right phase as the observed (Delworth and Knutson 2000; Delworth and Mann 2000), but many other realizations that do not. So when ensemble averaged, this internal variability is much reduced. Nevertheless, it shows that some models can produce such a multidecadal oscillation without anthropogenic forcing. To circumvent the known difficulty of model internal variability not always of the right phase and amplitude as the one realization that is our observed world, DelSol et al. (2011) analyzed the control runs of the coupled atmosphere–ocean general circulation models in phase 3 of the Coupled Model Intercomparison Project (CMIP3) archive (Meehl et al. 2007). They found, by maximizing the average predictability time, a dominant spatial pattern that they called the internal multidecadal pattern, which is centered at the North Atlantic but also extends to the Pacific. When the global temperature data are projected onto this spatial pattern, they obtain 2.5 cycles of a multidecadal oscillation very similar to the AMO index. Their result suggests that the oscillation is not anthropogenically forced.

I can only say that my understanding of this argument is that (a) it shows up in some models, but I don’t understand how this is relevant to whether it is an effect of temperature (b) some model that attributes it to temperature has problems (also not relevant) and (c) it appears in the pre-industrial era (again, if it is responsive to temperature I can’t imagine how this would be relevant to the question of whether it relates to a temperature signal or not). It still seems that they can’t explicitly state the criticism. They open with:

The remaining question is whether the AMO is a natural oscillation or the response to a time-varying anthropogenic forcing.

The way this is phrased does not seem to match how I understand the criticism of their conclusions.

[Response: I’d say the case is way overstated. The paper by Tung and Zhou, for instance, claims continual AMO visible in CET but their case is “totally weak.” Those who claim AMO is a climate driver rather than response do so, in my opinion, more through wishful thinking than through rigorous analysis, and lack the genuine skepticism which makes science strong.

There’s also the fact that in terms of its rapid fluctuations, the correlation of AMO to temperature is strongest at *negative* lag. That doesn’t flatter the case for causality.

And of course there’s the fact that AMO is *temperature* — nothing more, nothing less. It’s not like ENSO, which can be completely characterized in many ways including those that use no temperature data at all (like the Southern Oscillation Index). Finding strong correlation between global temperature and regional temperature is hardly worth crowing about.

Finally, there’s the question of physics. It’s rather important, I’d say. Global temperature increase is *energy* increase. Where did that energy come from? The glib answer “changes in AMOC” is no answer at all — such changes do not create energy out of nothing, and in the past (paleo) we’ve seen that temperature changes *induced* by AMOC changes will warm one region while cooling another. Are we really to believe that for no apparent reason, the AMO is warming up the *entire planet* — including the *oceans* — including the *deep ocean* — through truly massive quantities of energy with no apparent origin?

I find the whole “AMO is responsible for part of the global temperature change” idea to be mathturbation of the worst kind, exploiting obvious correlation between temperature and temperature to fly in the face of the laws of physics.]

Thank you for quoting the section. I agree that it is rather weak but there is a serious ‘system identification’ question here. On long enough time scales AMOC/THC transports heat from one part of the globe to another. The time scale is centennial to millennial. Humans have not (yet) added enough excess for it to begin to appear at the southern end of the AMOC ‘pipe’, I think.

Some AOGCM runs suggest we may expect AMOC slowdown due to global warming. At the same time, one does not expect AMOC to run at a nearly constant rate. So what could one hope to use to measure AMOC variations? The various papers under discussion here offer alternatives, all the way from all of AMO to just four surface stations (in Wood et al. (2010). One possibility is to use SSTs for just the two regions of deep water formation in the North Atlantic and correcting for (possibly) global SSTs to obtain just the variation, roughly as in Ting et al. (2009).

Paleo data from Greenland is not supportive of the use of the AMO in the manner done by Tung & Zhao. The analysis by Chylek et al. (2012) suggests are rather subdued role, at best, for a 50–80 year quasiperiod oscillation in deep water formation areas. The Dye 3 data ought to be the most important indicator; this suggests a 20 year quasiperiod for the past several hundred years. Tung & Zhuao attempt to discount the Chylek et al. analysis; I take it as insufficiently argued, at best.

I agree that it’s odd to attribute a trend to an oscillation, and odder still to suppose the oscillation creates all the extra energy. This:
“correlation between global temperature and regional temperature” and then drawing substantive inferences — sounds like there is a circular argument hiding in there somewhere. That could explain how they (appear to) circumvent conservation of energy. I sense a really neat paper coming on. As background, Key role of the Atlantic Multidecadal Oscillation in 20th century drought and wet periods over the Great Plains does match some things with the AMO, while on the other hand one wouldn’t really expect the AMO to melt the Arctic.

David, whenever anew comment draws me back to this thread, this statement:On long enough time scales AMOC/THC transports heat from one part of the globe to another. The time scale is centennial to millennial. Humans have not (yet) added enough excess for it to begin to appear at the southern end of the AMOC ‘pipe’, I think.
makes me blink.

You must have been thinking of distance and current speeds, but still, global warming is, well, global and the Atlantic, Pacific & Indian Oceans extend clear to the Southern Ocean. Figure 1 here:http://www.aoml.noaa.gov/phod/docs/Garzoli_progressing_towards.pdf
shows warm Atlantic surface currents, but it looks like not too much crosses the equator moving south. This supports your point in part, but –

The Southern Ocean has none the less been affected by subducted, advected heat. Mid-deep water (pushed down with its surface heat at the western end of the La Niña bulge) is advected into the Southern ocean) is drawn into the Antarctic currents … water reaching glacier fronts in Pine Island Bay is warmer, and the glaciers retreat.

Even though there are currents from one ocean to another, surely just some portion of the increased ocean heat content that I can’t quantify is due to ENSO and in particular La Niña. [Other things being equal, there will be greater net heat transfer into the colder-overall ocean surface during La Niña.] But to help get the heat down deep – This linkhttp://www.pmel.noaa.gov/tao/elnino/la-nina-story.html
and the figure with the three panels shows what I see happening: During La Niña the warmer water, pushed by strong trade winds, piles up against the Maritime Continent. But it doesn’t just pile up for months, some is pushed down, I surmise, where it mixes into “mid-deep” pacific water. Or in any case, with stronger upwelling of cold water along the west coast of South America during La Niña, other water must go down to replace what comes up, and this water will be warmer than what was down there before. QED ;)

Is there any indication that the ‘fluctuations’ are beginning to fluctuate more, or any reason to suspect that they might begin to do so in the future?
I see no obvious indication (merely by looking) that the former is happening in the data thus far for the US and Australia, and no doubt Tamino would have picked it up if such were so. But if/when large scale changes to the Earth’s surface occur – loss of Arctic sea-ice, large scale changes in vegetation cover, changes in ocean currents etc. – should we not expect also for the fluctuations, the standard deviation, to change?
Not that it isn’t bad enough already … .

It’s difficult to detect significant changes in the standard deviation with our limited records, but I just read a 2004 Nature paper that suggests the possibility of large increases in variability, at least in summer and at least over Europe (probably would be similar over other continental regions): http://www.nature.com/nature/journal/v427/n6972/abs/nature02300.html
They use a regional climate model and find that “temperature variability increases by up to 100%” by 2071-2100. It seems like the increased variability is related to droughts and feedbacks between soil moisture anomalies and temperature. So yeah, that is a little scary if it turns out to be true.

This is only just on topic; I’m looking at the model for the noise described in your paper: “Global temperature evolution 1979–2010″, Foster and Rahmstorf (2011); and the methods section for estimating “the number of data per effective degree of freedom”.

You consider an AR(1) model for noise first, and then conclude that the noise is significantly different from AR(1), by referring to figure A.1, a plot of autocorrelation co-efficients vs lags.

In a pure AR(1) process, these co-efficients should decay exponentially.

It bothers me that your comparison of the real co-efficients (black) with an AR(1) model (red) seems to take the AR(1) model by fitting an exponential simply to the first autocorrelation co-efficient.

When you are working from data, these co-efficients are not going to be perfect guides to the noise. Why don’t you simply fit an exponential to all the calculated co-efficients, and call THAT the AR(1) model? It would have a larger autoregression co-efficient, so that the red plot would be raised to be a better match to the calculated value,

I’m only just starting to learn about autocorrelation (and I do plan to buy your book when I can scape some money together!). So this is a genuine question. Thanks for any help.

And thanks for this post. I’m in Australia, and I feel like a hypocrite every time I put on the air conditioning… using up more power to solve the short term heat issue exacerbated because of our excessive use of power.

[Response: If I’m not mistaken, estimating the autoregression parameter from the 1st sample autocorrelation alone is the maximum-likelihood estimate. More to the point, that’s how it’s actually done in practice. In any case, for global temperature data an ARMA(1,1) model is significantly better than AR(1), however the AR(1) coefficient is estimated. I’d venture to say that neither can be regarded as “truth” — but the ARMA(1,1) model is more useful.]

Charts that show anomalies can be useful in identifying deviations from trend but can mislead in a similar way to charts with a suppressed origin. Suppose that without GHGs max heatwave temp would have been 94 degrees F and with GHGs it is 96. This can appear dramatic – or not – depending on the scaling of the anomaly or the choice of origin. Whether or not such an increase it is a “disaster'” depends on the local/regional/global environmental response to a 2 degree increase in temperature, not the scaling of the y axis. The response could conceivably range from beneficial to devastation (e.g. as a result of ice melt). And assessing what constitutes a disaster or devastation depends on some context. Millions will die this year as a result of poverty. (I know you regard this as “concern trolling” . All I can say is that I can’t see why it is not a legitimate point.) Basically, the charts in the post are rhetorical devices that add nothing to understanding of the seriousness of the problem. (For the avoidance of doubt I favour the imposition of significant and increasing carbon taxes, levied at the border on imports from non-compliant countries. But I just wish I didn’t have to say that.)

[Response: The graphs in this post illustrate perfectly the point of this post: that when trend and fluctuation go in the same direction, the result can often be unprecedented extremes. Your trivializing them as “rhetorical devices that add nothing to understanding” suggests that either you didn’t get the point, or you don’t want to.

History has proved again and again that extreme extreme weather is disastrous. If you want to put that in a modern context, go to the midwest and ask a corn farmer whether last summer’s drought was “beneficial,” or travel to the New Jersey coast and inquire about the benefit of hurricane Sandy.

Your mention of “millions will die of poverty” is indeed concern trolling, of the worst kind. You might as well have mentioned that thousands, perhaps millions, of innocent children will suffer the horror of child sexual abuse. Just what the fuck does either of those issues have to do with the fact that the collision of trend and fluctuation leads to unprecedented extremes?

You just wanted to belittle the seriousness of the climate problem by raising the spectre of some other problem. Again, if you don’t see why it’s not a legitimate point that’s because you don’t want to. If poverty were really your concern, you’d be talking about it on some blog where that’s the subject, and/or you’d open your eyes to the fact that man-made climate change will throw lots more people into that unenviable condition, and make things a helluva lot worse for those who are already there.

You don’t have to say that you favor carbon taxes, but you really should stop raising issues that are irrelevant to the science and the danger of climate change, and stop slandering graphics which honestly make the relevant point, the very core subject of this post, crystal-clear.]

What you are missing is that where moving the origin for a zero-trend dataset does indeed ‘make things look worse’, when the trend in the data ‘moves the origin’, it really does make things worse. One is presentation, the other is substance.

WRT heatwaves, the problem is not so much that of the peak moving from (for instance) 42 to 45 degrees. It’s that the period of time over 40 degrees may go from 1 to 10 days with massive consequences.

As far as the whole poverty thing goes.. there is insufficient fossil fuel for the whole world to have a 1st world standard of living for more than a couple of decades if that, even if global warming was not an issue. Hence, trying to raise living standards by burning fossil fuels – even if that would work in the short term – is not the way to go, and by extension there is not a choice between ‘Fixing global warming’ and ‘Relieving poverty’ to be made.

Jonp, your concern for the poor is admirable. What action have you taken to address it? If you are not actively involved, then indeed, your invocation is concern trolling.

More to the point, the poorest in the world are subsistence farmers with little access to global markets, imported food or healthcare. Since most crop yields–especially in tropical areas, where most of the poor reside–decline with increasing temperature, then should you not be concerned about warming? And since climate change seems to exacerbate weather extremes–e.g. drought and episodic heavy precipitation–and since these events facilitate increased pests such as anopheles mosquitoes that carry malaria, should you not be concerned about climate change. It is the precisely the poor who will suffer the most from the effects of climate change and who have the least margin to overcome these effects.

The point about poverty is that higher energy costs will increase it. So we need to accept there are morally significant trade-offs. I should have made that clear. One of the attractions of making carbon taxes the central mitigation measure is that the revenues can be re-cycled to offset such effects.

I won’t try and respond to the rest – but you are making assumptions about my motivation which I know to be incorrect.

The point about poverty is that global warming will increase it, and I don’t see any of those in the developed world who are so concerned about poverty lining up to donate their fossil fuel quota to those in poverty so that those they think need it the most can actually use it.

In fact, one of the most common arguments from the developed world is “Why should we reduce our usage when countries like China are rapidly increasing theirs?”

jonp, Just curious. Did you read my post? I specifically pointed out how climate change would make the poorest even poorer. The poorest in the world do not care about energy prices–their energy comes from firewood–gathered from ever more distant locations as their environs become more deforested. And they care about the meager harvest they can scrape from their tiny plots of land with their bare hands and a few simple hand tools. That harvest will suffer as temperatures warm and as ever more violent storms strip away what little topsoil remains.

Aside from wood for heating, the most poverty-stricken have had to use kerosene lamps for lighting which have adverse health effects due to smoke, and cause horrific burns in accidents. The kerosene has to be acquired from many miles away and usually transported on foot, while the price fluctuates generally upward. The majority of these people will never be “on the grid” in our lifetimes.

Cheap solar PV, however, lets the laws of physics deliver the energy to their door, is free after the initial investment, does not burn kids in accidents or cause them chest problems, can charge mobile phones which have become part and parcel of remote commerce and money transfer, and means children can stay study longer into the night which has obvious longer term benefits to their society as a whole.

“The World Bank estimates that, as a result, 780 million women and children inhale smoke which is equivalent to smoking 2 packets of cigarettes every day. 60% of adult, female lung-cancer victims in developing nations are non-smokers. The fumes also cause eye infections and cataracts, but burning kerosene is also more immediately dangerous: 2.5 million people a year, in India alone, suffer severe burns from overturned kerosene lamps. Burning Kerosene also comes with a financial burden: kerosene for lighting ALONE can consume 10 to 20% of a household’s income. This burden traps people in a permanent state of subsistence living, buying cupfuls of fuel for their daily needs, as and when they can.

The burning of Kerosene for lighting also produces 244 million tonnes of Carbon Dioxide annually.”

In Bangladesh micro-solar systems are being installed at a rate of over 1,000 per day. They have provided over 1 million homes and small businesses with standalone solar systems. Purchasers pay for the system over time and the payments are less than what they had been spending for kerosene.

This is a winner. It cuts both CO2 and black carbon/soot. It improves people’s lives by giving them better quality light, reduces health problems, and frees up their very limited money for other uses. It’s paying its own way and creating jobs.

Sheikh’s doubled his income since signing up for a Grameen Shakti SHS plan that enables him to pay for the solar power system with a small down payment and affordable monthly installments.

Sheikh pad the Bangladeshi Taka equivalent of $24 up-front for an SHS system comprising a 20-Watt solar PV panel, battery, regulator, CFLs and LEDs. He’ll pay another $5 month over the next 36 months to pay off the total cost.

Grameen Shakti’s most popular SHS system provides about 10W of clean, renewable electric power for a total cost of $124. That ranges up to the most expensive system, which provides 135W of uninterrupted power for four four hours at a total cost of $925.

“I’m personally more worried that the energy will find a way into the GIS or even moreso the WAIS in a way that takes us by surprise.”

Don’t be worried: That’s the event that might wake up the majority or people to force their governments, and themselves, to actually reduce emissions and start adapting in earnest. In fact, the effort needed to adaptat to sea level rise could be enough all by itself to kill our planet killing global economy.

A real extreme extreme experience. Remember me with that ugly exterminate post ? Maybe the heat was getting to me.

Live in bush in AUS, North NSW, 60k from coast. During this current heatwave, I have had multiple groups of 48 degree days and when it gets to 48 outside, it is at least 52 in my shadecloth-wall loungeroom. This century, around 40 is not unusual, but my poor body is having a real hard time coping with 50, specially when it drops back to 20 at night.

I do not use airconditioning, cause that does not fit with sustainable living. Your graphs of extremes have again confirmed my plans. The only safe place to be in this heat is under the ground. Not dead, but in a bunker.

All very entertaining these global warming debates, but when are we actually going to do something about it ? These blogs help inform the public. I would say that the bulk of the voting public does not come near any of these sites and even if they did, they would loose interest after a few sentences with numbers. Yes, they hear the headlines and immediately wonder what exiting thing will be on tomorrow.

Best direction is your post suggesting that the Aussies kick Graig out-of-office. That needs the voting public. The Conversation currently has an article going ferral at https://theconversation.edu.au/humanitys-scorched-earth-program-where-to-now-11525, related to more extreme bush fires due to global warming. At least that sentiment in my ugly post is slowly warming too. In Aus after any big fire, they are always looking for who to blame. If that can clearly be attributed to Global Warming, then who is opposing that ?

Luckily for me, the heatwave has passed, cause the monsoon has finally started. All I need to worry about now is that 18 meters of water over the bridge going to town :)

What should be mentioned in discussion of fluctuations and extremes is the notion of black swan events (highly improbable, but still within a current climate regime) and dragon-king events (which are also highly improbable, but actually represent a climate regime change). Climate is far more than just the average weather, for it represents the net sum of all forcings along with all related feedbacks, and as such, represents a dynamical regime. When those forcings change the regime changes. Regime changes are ushered in by a series of highly improbable events (black swans) which culminate in an event that only in retrospect can be seen as not just another black swan but a dragon-king event- a regime change. An example or this would be Arctic sea ice over the past 10 years. We saw a steadily declining summer sea ice which were black swans when compared to the longer term sea ice extent. Then 2007 hit (or 2010 by some account if you look at sea ice volume). One of these years can now be seen as a dragon-king event, in which the dynamic regime of the Arctic sea ice changed. 2012, though very low by pre-2007 standards, is actually now the norm of this new regime. However, based on how quickly the Arctic sea ice regime is changing, a new, seasonal ice-free Arctic regime is likely right around the corner.

For more on the differences between black swans and dragon-kings, see:

There is also a trend in the Arctic sea ice an Arctic snow cover. Soon the Arctic will be more-or-less ice free in summer. Snow in Arctic regions is also melting much earlier. (I understand these particularly from Neven’s sea ice blog).

Yes, there is speculation there that the changes in the Arctic will end up changing the number of Hadley cells in the Northern hemisphere, and therefore significantly change regional climate over a fair chunk of the Earth’s surface.

I will confess to having no clue as to the reality or otherwise of this…

Regarding the second last figure one could point out that “skeptics” also use the deviation between the observed and projected curves for the temperatures, like it can be seen for the recent decade, as “argument” to claim that Nature falsifies the models. They totally ignore that the projections are the average of many model realizations. So effectively it’s the same as applying a low-pass filter to a time series, whereas Nature provides only one single realization. We can’t re-run Nature with randomly perturbed initial conditions, unlike we can do it with the models.

Well, Hello Death-Valley
Hello Death-Valley
It’d be nice to have you back where you belong
You’re like Hell, Death Valley…..I can tell, Death Valley
You’re still roastin’…you’re still toastin’…you’re still goin’ strong
I feel my head swayin’…while for cold I’m prayin’
For one of your old records from way back when
So…golly, gee, fellas….down on bended knee, fellas
Death Valley’ll never go away….I said she’ll never go away
Death Valley’ll never go away again

…From what I can tell, in this case, the multiple regression approach used by Foster and Rahmstorf (2011) [and Lean and Rind (2008), although I haven’t investigated the specifics of that paper] can produce misleading results, even failing to recognize a pause in the underlying signal. In those cases, the “reconstruction” can be a worse representation of the true signal than the original, unadjusted results, and should not be used to test projections. Of course, in this particular case, much of it seems to stem from a lingering effect of the Pinatubo recovery into the 21st century, which I am currently skeptical exists in the real world.

the probability of two successive bad years is even more sensitive to changes in the mean [than the probability of a single bad year, being multiplicative for independent events]. The importance of successive extremes lies in their cumulative impact: an agricultural region may be able to understand a single shock, but if buffer stores are depleted by one bad season, a second one in succession may be far more devastating.

Even though the probability of a succession of extreme events may still be relatively small after the shift in the mean, it increases very quickly (much faster than linearly) with such a shift.

From one extreme extreme to the next. Theory and discusssion is great but nothing beats the actual experience. Yes, Horatio, Queensland is about to experience their succession event. The dams are overflowing and the coffers are empty. This time they are having a little extra, like 7 tornadoes on Saturday. And for a real life experience, the eye of that tropical low (ex cyclone) will be above me sometime tomorrow afternoon. As a warmup, today in 11 hours, some 50 olympic swimming pools came tumbling out of the sky. Suppose there will be no beer and barbie for me to celebrate Aussie day. Let’s hope that this one leaves a clear message.

January 2011 – “A series of floods hit Australia, beginning in December 2010, primarily in the state of Queensland including its capital city, Brisbane. The floods forced the evacuation of thousands of people from towns and cities. At least 70 towns and over 200,000 people were affected. Damage initially was estimated at around A$1 billion. The estimated reduction in Australia’s GDP is about A$30 billion”

March 2010 – “The floods, described by the Queensland Minister for Primary Industries Tim Mulherin as the “worst flood in 120 years” are however expected to provide a billion dollar boost to the local economy, following the “worst drought since Federation”

Look on the bright side – the climate cranks can dust off their “not caused by global warming” articles from 2010.

“millions will die of poverty”
No. Millions will die of extreme weather events that they can’t cope with because they live in poverty. Heat stroke, because the can’t afford refrigeration or air conditioning, malnutrition/starvation because AGW caused drought made the crops fail, and they can’t afford to buy other food because they live in poverty.http://web.ics.purdue.edu/~hertel/data/uploads/publications/erl-ahmed-diffenbaugh-hertel.pdf
“Extreme climate events could influence poverty by affecting agricultural productivity and raising prices of staple foods that are important to poor households in developing countries.”
“We find that extremes under present climate volatility increase poverty across our developing country sample—particularly in Bangladesh, Mexico, Indonesia, and Africa—with urban wage earners the most vulnerable group. We also find that global warming exacerbates poverty vulnerability in many nations.”
Note that AGW not only disproportionately affects the poor, it creates more poor people. Fighting poverty while ignoring the poverty caused by AGW is pissing into the wind. Curing poverty by raising the world standard of living to air conditioning, two cars in the garage, and all the other fossil fueled comforts of Western “Civilization” is a fool’s mission.

This ‘millions will die of poverty’ meme really ticks me off. The reality is, millions have been dying of poverty all along and who, among these noble advocates, gave a crap then?

Similarly, the folks who suddenly care about bird and bat deaths when the COD happens to be wind turbines, or about desert tortoises when a solar farm is proposed, or about third-world sweatshops when the sweatshop is a recycling operation, or about mercury when the subject is CFLs. Let me be clear that I’ve got no beef with anyone who is really concerned about these things–but not so with those who (respectively) ignore bird deaths due to collision with other structure (orders of magnitude greater in number), challenges to desert ecologies due to real estate developments (ditto), third-world sweatshops making just about anything else, or about mercury emitted by burning coal (again, orders of magnitude greater than any hazard from CFLs.)

Millions will die of poverty
From warming mitigations
Millions will die from CFLs
From mercury sensations
Millions of birds will bite the dust
From wind farm turbinations
Millions will buy this phony cry
From Big Oil Pub. Relations

Adaptation to extreme extremes.
On 27 Jan, the 1km wide Clarence river peaked at 8.08 meters, just 12cm below the Grafton Levee. This new peak has not been seen in white history. Grafton survives, but downstream it is a different case.http://www.dailyexaminer.com.au/news/ulmarra-floods-of-54-used-as-a-benchmark/1735982/
Local rag shows picture of 4 year old boy. He has seen an extreme flood every summer. Soon he will join the older kids to play with surfboards and dinghies.
Adaptation to extreme extremes. Humanity will survive ( for a while ).